load("XSTSF_production.RData")
f0_mono_pre <- f0_mono_pre %>%
mutate(citation_tone_sync = substr(citation_tone, 1, 2),
ind_no = paste0(speaker, '_', citation_no)) %>%
# normalisation
group_by(speaker) %>%
mutate(norm_f0 = scale(log(f0))) %>%
ungroup()
kable(f0_mono_pre[1:200,]) %>%
kable_styling("striped", full_width = F) %>%
scroll_box(width = '800px', height = "250px")
| speaker | citation_no | time | f0 | token | citation_tone | citation_tone_sync | ind_no | norm_f0 |
|---|---|---|---|---|---|---|---|---|
| S1 | 1 | 1 | 244.5355 | 青 | HHp | HH | S1_1 | -1.230805122 |
| S1 | 1 | 2 | 265.5099 | 青 | HHp | HH | S1_1 | -0.623044344 |
| S1 | 1 | 3 | 262.8037 | 青 | HHp | HH | S1_1 | -0.698706015 |
| S1 | 1 | 4 | 267.3166 | 青 | HHp | HH | S1_1 | -0.572958412 |
| S1 | 1 | 5 | 274.9259 | 青 | HHp | HH | S1_1 | -0.365664839 |
| S1 | 1 | 6 | 278.1372 | 青 | HHp | HH | S1_1 | -0.279898982 |
| S1 | 1 | 7 | 277.2501 | 青 | HHp | HH | S1_1 | -0.303490378 |
| S1 | 1 | 8 | 276.2189 | 青 | HHp | HH | S1_1 | -0.331011101 |
| S1 | 1 | 9 | 276.3570 | 青 | HHp | HH | S1_1 | -0.327320905 |
| S1 | 1 | 10 | 276.4264 | 青 | HHp | HH | S1_1 | -0.325464757 |
| S1 | 3 | 1 | 254.0659 | 书 | HHp | HH | S1_3 | -0.948434523 |
| S1 | 3 | 2 | 246.6589 | 书 | HHp | HH | S1_3 | -1.166952628 |
| S1 | 3 | 3 | 254.1301 | 书 | HHp | HH | S1_3 | -0.946570304 |
| S1 | 3 | 4 | 265.6612 | 书 | HHp | HH | S1_3 | -0.618836683 |
| S1 | 3 | 5 | 278.0189 | 书 | HHp | HH | S1_3 | -0.283040004 |
| S1 | 3 | 6 | 289.1111 | 书 | HHp | HH | S1_3 | 0.005894237 |
| S1 | 3 | 7 | 296.0174 | 书 | HHp | HH | S1_3 | 0.180244179 |
| S1 | 3 | 8 | 299.3299 | 书 | HHp | HH | S1_3 | 0.262430821 |
| S1 | 3 | 9 | 299.0619 | 书 | HHp | HH | S1_3 | 0.255814578 |
| S1 | 3 | 10 | 295.3790 | 书 | HHp | HH | S1_3 | 0.164298324 |
| S1 | 5 | 1 | 287.6011 | 椒 | HHp | HH | S1_5 | -0.032779365 |
| S1 | 5 | 2 | 279.6140 | 椒 | HHp | HH | S1_5 | -0.240787055 |
| S1 | 5 | 3 | 289.4503 | 椒 | HHp | HH | S1_5 | 0.014554257 |
| S1 | 5 | 4 | 295.1713 | 椒 | HHp | HH | S1_5 | 0.159104081 |
| S1 | 5 | 5 | 293.6183 | 椒 | HHp | HH | S1_5 | 0.120144690 |
| S1 | 5 | 6 | 290.7363 | 椒 | HHp | HH | S1_5 | 0.047294149 |
| S1 | 5 | 7 | 290.0435 | 椒 | HHp | HH | S1_5 | 0.029674307 |
| S1 | 5 | 8 | 290.4950 | 椒 | HHp | HH | S1_5 | 0.041163200 |
| S1 | 5 | 9 | 292.5095 | 椒 | HHp | HH | S1_5 | 0.092201750 |
| S1 | 5 | 10 | 285.1681 | 椒 | HHp | HH | S1_5 | -0.095525967 |
| S1 | 7 | 1 | 271.1185 | 苦 | HHs | HH | S1_7 | -0.468660035 |
| S1 | 7 | 2 | 287.2155 | 苦 | HHs | HH | S1_7 | -0.042690068 |
| S1 | 7 | 3 | 302.9914 | 苦 | HHs | HH | S1_7 | 0.352223653 |
| S1 | 7 | 4 | 314.3481 | 苦 | HHs | HH | S1_7 | 0.623981713 |
| S1 | 7 | 5 | 321.2062 | 苦 | HHs | HH | S1_7 | 0.783379283 |
| S1 | 7 | 6 | 324.0588 | 苦 | HHs | HH | S1_7 | 0.848678631 |
| S1 | 7 | 7 | 323.6683 | 苦 | HHs | HH | S1_7 | 0.839772256 |
| S1 | 7 | 8 | 319.9600 | 苦 | HHs | HH | S1_7 | 0.754667911 |
| S1 | 7 | 9 | 311.5997 | 苦 | HHs | HH | S1_7 | 0.559126558 |
| S1 | 7 | 10 | 296.3532 | 苦 | HHs | HH | S1_7 | 0.188618025 |
| S1 | 9 | 1 | 281.0815 | 包 | HHp | HH | S1_9 | -0.202127105 |
| S1 | 9 | 2 | 267.8389 | 包 | HHp | HH | S1_9 | -0.558542942 |
| S1 | 9 | 3 | 275.0358 | 包 | HHp | HH | S1_9 | -0.362712863 |
| S1 | 9 | 4 | 287.0520 | 包 | HHp | HH | S1_9 | -0.046894151 |
| S1 | 9 | 5 | 293.1499 | 包 | HHp | HH | S1_9 | 0.108351595 |
| S1 | 9 | 6 | 293.6366 | 包 | HHp | HH | S1_9 | 0.120604831 |
| S1 | 9 | 7 | 292.3401 | 包 | HHp | HH | S1_9 | 0.087923968 |
| S1 | 9 | 8 | 291.1803 | 包 | HHp | HH | S1_9 | 0.058565186 |
| S1 | 9 | 9 | 290.7635 | 包 | HHp | HH | S1_9 | 0.047986210 |
| S1 | 9 | 10 | 283.6640 | 包 | HHp | HH | S1_9 | -0.134581226 |
| S1 | 11 | 1 | 271.1616 | 手 | HHs | HH | S1_11 | -0.467484461 |
| S1 | 11 | 2 | 278.9779 | 手 | HHs | HH | S1_11 | -0.257608986 |
| S1 | 11 | 3 | 293.5877 | 手 | HHs | HH | S1_11 | 0.119373141 |
| S1 | 11 | 4 | 306.4353 | 手 | HHs | HH | S1_11 | 0.435694369 |
| S1 | 11 | 5 | 316.3603 | 手 | HHs | HH | S1_11 | 0.671106831 |
| S1 | 11 | 6 | 322.3060 | 手 | HHs | HH | S1_11 | 0.808622637 |
| S1 | 11 | 7 | 327.2754 | 手 | HHs | HH | S1_11 | 0.921624447 |
| S1 | 11 | 8 | 327.5372 | 手 | HHs | HH | S1_11 | 0.927530103 |
| S1 | 11 | 9 | 319.8704 | 手 | HHs | HH | S1_11 | 0.752600195 |
| S1 | 11 | 10 | 299.9994 | 手 | HHs | HH | S1_11 | 0.278929783 |
| S1 | 13 | 1 | 268.2387 | 瓜 | HHp | HH | S1_13 | -0.547527218 |
| S1 | 13 | 2 | 281.0335 | 瓜 | HHp | HH | S1_13 | -0.203388547 |
| S1 | 13 | 3 | 294.3656 | 瓜 | HHp | HH | S1_13 | 0.138918363 |
| S1 | 13 | 4 | 303.1603 | 瓜 | HHp | HH | S1_13 | 0.356338639 |
| S1 | 13 | 5 | 309.5507 | 瓜 | HHp | HH | S1_13 | 0.510400473 |
| S1 | 13 | 6 | 312.4849 | 瓜 | HHp | HH | S1_13 | 0.580078668 |
| S1 | 13 | 7 | 311.6507 | 瓜 | HHp | HH | S1_13 | 0.560334185 |
| S1 | 13 | 8 | 309.3480 | 瓜 | HHp | HH | S1_13 | 0.505564591 |
| S1 | 13 | 9 | 306.0085 | 瓜 | HHp | HH | S1_13 | 0.425401770 |
| S1 | 13 | 10 | 291.5438 | 瓜 | HHp | HH | S1_13 | 0.067778117 |
| S1 | 15 | 1 | 265.5595 | 樱 | HHp | HH | S1_15 | -0.621665143 |
| S1 | 15 | 2 | 275.3815 | 樱 | HHp | HH | S1_15 | -0.353435447 |
| S1 | 15 | 3 | 295.0454 | 樱 | HHp | HH | S1_15 | 0.155953520 |
| S1 | 15 | 4 | 310.9354 | 樱 | HHp | HH | S1_15 | 0.543364480 |
| S1 | 15 | 5 | 325.5956 | 樱 | HHp | HH | S1_15 | 0.883619774 |
| S1 | 15 | 6 | 334.4504 | 樱 | HHp | HH | S1_15 | 1.081789756 |
| S1 | 15 | 7 | 338.1307 | 樱 | HHp | HH | S1_15 | 1.162616410 |
| S1 | 15 | 8 | 339.9204 | 樱 | HHp | HH | S1_15 | 1.201602948 |
| S1 | 15 | 9 | 330.6185 | 樱 | HHp | HH | S1_15 | 0.996683732 |
| S1 | 15 | 10 | 307.2528 | 樱 | HHp | HH | S1_15 | 0.455373029 |
| S1 | 17 | 1 | 277.0011 | 机 | HHp | HH | S1_17 | -0.310125704 |
| S1 | 17 | 2 | 283.1580 | 机 | HHp | HH | S1_17 | -0.147768201 |
| S1 | 17 | 3 | 302.7466 | 机 | HHp | HH | S1_17 | 0.346254592 |
| S1 | 17 | 4 | 315.6392 | 机 | HHp | HH | S1_17 | 0.654254011 |
| S1 | 17 | 5 | 326.2853 | 机 | HHp | HH | S1_17 | 0.899248174 |
| S1 | 17 | 6 | 333.4016 | 机 | HHp | HH | S1_17 | 1.058594061 |
| S1 | 17 | 7 | 333.5355 | 机 | HHp | HH | S1_17 | 1.061558244 |
| S1 | 17 | 8 | 328.1010 | 机 | HHp | HH | S1_17 | 0.940232270 |
| S1 | 17 | 9 | 323.1418 | 机 | HHp | HH | S1_17 | 0.827749143 |
| S1 | 17 | 10 | 305.4540 | 机 | HHp | HH | S1_17 | 0.412005792 |
| S1 | 19 | 1 | 265.9029 | 花 | HHp | HH | S1_19 | -0.612121412 |
| S1 | 19 | 2 | 274.9813 | 花 | HHp | HH | S1_19 | -0.364176349 |
| S1 | 19 | 3 | 295.3610 | 花 | HHp | HH | S1_19 | 0.163849336 |
| S1 | 19 | 4 | 310.9778 | 花 | HHp | HH | S1_19 | 0.544372631 |
| S1 | 19 | 5 | 320.7755 | 花 | HHp | HH | S1_19 | 0.773469513 |
| S1 | 19 | 6 | 325.1745 | 花 | HHp | HH | S1_19 | 0.874061293 |
| S1 | 19 | 7 | 323.3176 | 花 | HHp | HH | S1_19 | 0.831767204 |
| S1 | 19 | 8 | 317.3004 | 花 | HHp | HH | S1_19 | 0.693020953 |
| S1 | 19 | 9 | 311.1757 | 花 | HHp | HH | S1_19 | 0.549071224 |
| S1 | 19 | 10 | 299.6288 | 花 | HHp | HH | S1_19 | 0.269801266 |
| S1 | 21 | 1 | 254.0509 | 海 | HHs | HH | S1_21 | -0.948872128 |
| S1 | 21 | 2 | 264.5050 | 海 | HHs | HH | S1_21 | -0.651048571 |
| S1 | 21 | 3 | 287.7159 | 海 | HHs | HH | S1_21 | -0.029833025 |
| S1 | 21 | 4 | 305.2054 | 海 | HHs | HH | S1_21 | 0.405992670 |
| S1 | 21 | 5 | 317.6704 | 海 | HHs | HH | S1_21 | 0.701629111 |
| S1 | 21 | 6 | 325.6137 | 海 | HHs | HH | S1_21 | 0.884029894 |
| S1 | 21 | 7 | 330.1072 | 海 | HHs | HH | S1_21 | 0.985253760 |
| S1 | 21 | 8 | 329.5035 | 海 | HHs | HH | S1_21 | 0.971735205 |
| S1 | 21 | 9 | 324.4411 | 海 | HHs | HH | S1_21 | 0.857386029 |
| S1 | 21 | 10 | 306.6209 | 海 | HHs | HH | S1_21 | 0.440167619 |
| S1 | 23 | 1 | 299.0016 | 菜 | HLq | HL | S1_23 | 0.254324561 |
| S1 | 23 | 2 | 334.0672 | 菜 | HLq | HL | S1_23 | 1.073322392 |
| S1 | 23 | 3 | 349.4912 | 菜 | HLq | HL | S1_23 | 1.406675168 |
| S1 | 23 | 4 | 350.7617 | 菜 | HLq | HL | S1_23 | 1.433475541 |
| S1 | 23 | 5 | 350.6263 | 菜 | HLq | HL | S1_23 | 1.430623916 |
| S1 | 23 | 6 | 346.5725 | 菜 | HLq | HL | S1_23 | 1.344737205 |
| S1 | 23 | 7 | 335.7906 | 菜 | HLq | HL | S1_23 | 1.111324915 |
| S1 | 23 | 8 | 319.1788 | 菜 | HLq | HL | S1_23 | 0.736614274 |
| S1 | 23 | 9 | 298.3476 | 菜 | HLq | HL | S1_23 | 0.238152571 |
| S1 | 23 | 10 | 277.7784 | 菜 | HLq | HL | S1_23 | -0.289432465 |
| S1 | 25 | 1 | 307.8745 | 带 | HLq | HL | S1_25 | 0.470299602 |
| S1 | 25 | 2 | 323.3637 | 带 | HLq | HL | S1_25 | 0.832819768 |
| S1 | 25 | 3 | 331.8331 | 带 | HLq | HL | S1_25 | 1.023766024 |
| S1 | 25 | 4 | 341.1990 | 带 | HLq | HL | S1_25 | 1.229332597 |
| S1 | 25 | 5 | 344.9423 | 带 | HLq | HL | S1_25 | 1.309916104 |
| S1 | 25 | 6 | 342.3283 | 带 | HLq | HL | S1_25 | 1.253735998 |
| S1 | 25 | 7 | 333.2632 | 带 | HLq | HL | S1_25 | 1.055527904 |
| S1 | 25 | 8 | 316.3533 | 带 | HLq | HL | S1_25 | 0.670944993 |
| S1 | 25 | 9 | 298.2870 | 带 | HLq | HL | S1_25 | 0.236653632 |
| S1 | 25 | 10 | 288.9571 | 带 | HLq | HL | S1_25 | 0.001959835 |
| S1 | 24 | 1 | 281.4118 | 草 | HHs | HH | S1_24 | -0.193452854 |
| S1 | 24 | 2 | 286.1060 | 草 | HHs | HH | S1_24 | -0.071275148 |
| S1 | 24 | 3 | 300.8087 | 草 | HHs | HH | S1_24 | 0.298828254 |
| S1 | 24 | 4 | 311.8729 | 草 | HHs | HH | S1_24 | 0.565598221 |
| S1 | 24 | 5 | 318.5808 | 草 | HHs | HH | S1_24 | 0.722763622 |
| S1 | 24 | 6 | 323.8336 | 草 | HHs | HH | S1_24 | 0.843544263 |
| S1 | 24 | 7 | 325.9339 | 草 | HHs | HH | S1_24 | 0.891289544 |
| S1 | 24 | 8 | 325.2983 | 草 | HHs | HH | S1_24 | 0.876873695 |
| S1 | 24 | 9 | 319.4159 | 草 | HHs | HH | S1_24 | 0.742099821 |
| S1 | 24 | 10 | 301.9351 | 草 | HHs | HH | S1_24 | 0.326430436 |
| S1 | 26 | 1 | 248.0613 | 桃 | RFp | RF | S1_26 | -1.125079001 |
| S1 | 26 | 2 | 229.9690 | 桃 | RFp | RF | S1_26 | -1.684389826 |
| S1 | 26 | 3 | 260.0222 | 桃 | RFp | RF | S1_26 | -0.777290552 |
| S1 | 26 | 4 | 291.0476 | 桃 | RFp | RF | S1_26 | 0.055197077 |
| S1 | 26 | 5 | 318.9533 | 桃 | RFp | RF | S1_26 | 0.731394055 |
| S1 | 26 | 6 | 338.3428 | 桃 | RFp | RF | S1_26 | 1.167248118 |
| S1 | 26 | 7 | 342.0703 | 桃 | RFp | RF | S1_26 | 1.248166343 |
| S1 | 26 | 8 | 332.1762 | 桃 | RFp | RF | S1_26 | 1.031399647 |
| S1 | 26 | 9 | 307.1932 | 桃 | RFp | RF | S1_26 | 0.453939620 |
| S1 | 26 | 10 | 271.3206 | 桃 | RFp | RF | S1_26 | -0.463155654 |
| S1 | 28 | 1 | 260.4315 | 莓 | RFp | RF | S1_28 | -0.765673540 |
| S1 | 28 | 2 | 283.8817 | 莓 | RFp | RF | S1_28 | -0.128916865 |
| S1 | 28 | 3 | 310.7712 | 莓 | RFp | RF | S1_28 | 0.539464179 |
| S1 | 28 | 4 | 334.2644 | 莓 | RFp | RF | S1_28 | 1.077682446 |
| S1 | 28 | 5 | 350.1192 | 莓 | RFp | RF | S1_28 | 1.419934078 |
| S1 | 28 | 6 | 350.8767 | 莓 | RFp | RF | S1_28 | 1.435895004 |
| S1 | 28 | 7 | 339.2072 | 莓 | RFp | RF | S1_28 | 1.186092481 |
| S1 | 28 | 8 | 321.2584 | 莓 | RFp | RF | S1_28 | 0.784578577 |
| S1 | 28 | 9 | 295.4549 | 莓 | RFp | RF | S1_28 | 0.166197920 |
| S1 | 28 | 10 | 270.4629 | 莓 | RFp | RF | S1_28 | -0.486540325 |
| S1 | 27 | 1 | 271.9794 | 水 | HHs | HH | S1_27 | -0.445243669 |
| S1 | 27 | 2 | 292.9754 | 水 | HHs | HH | S1_27 | 0.103955307 |
| S1 | 27 | 3 | 313.3579 | 水 | HHs | HH | S1_27 | 0.600681337 |
| S1 | 27 | 4 | 324.7230 | 水 | HHs | HH | S1_27 | 0.863800872 |
| S1 | 27 | 5 | 333.9893 | 水 | HHs | HH | S1_27 | 1.071601192 |
| S1 | 27 | 6 | 340.7481 | 水 | HHs | HH | S1_27 | 1.219565562 |
| S1 | 27 | 7 | 343.6093 | 水 | HHs | HH | S1_27 | 1.281321195 |
| S1 | 27 | 8 | 342.9812 | 水 | HHs | HH | S1_27 | 1.267807468 |
| S1 | 27 | 9 | 337.1363 | 水 | HHs | HH | S1_27 | 1.140864079 |
| S1 | 27 | 10 | 318.4932 | 水 | HHs | HH | S1_27 | 0.720734557 |
| S1 | 30 | 1 | 225.3634 | 房 | RFp | RF | S1_30 | -1.833800311 |
| S1 | 30 | 2 | 199.4391 | 房 | RFp | RF | S1_30 | -2.736343044 |
| S1 | 30 | 3 | 228.6651 | 房 | RFp | RF | S1_30 | -1.726386324 |
| S1 | 30 | 4 | 262.2391 | 房 | RFp | RF | S1_30 | -0.714588700 |
| S1 | 30 | 5 | 284.0372 | 房 | RFp | RF | S1_30 | -0.124872173 |
| S1 | 30 | 6 | 285.8136 | 房 | RFp | RF | S1_30 | -0.078826447 |
| S1 | 30 | 7 | 280.0584 | 房 | RFp | RF | S1_30 | -0.229058408 |
| S1 | 30 | 8 | 277.5319 | 房 | RFp | RF | S1_30 | -0.295987734 |
| S1 | 30 | 9 | 276.0606 | 房 | RFp | RF | S1_30 | -0.335246281 |
| S1 | 30 | 10 | 278.1836 | 房 | RFp | RF | S1_30 | -0.278665963 |
| S1 | 32 | 1 | 264.3931 | 牛 | RFp | RF | S1_32 | -0.654175270 |
| S1 | 32 | 2 | 295.0272 | 牛 | RFp | RF | S1_32 | 0.155498705 |
| S1 | 32 | 3 | 327.1467 | 牛 | RFp | RF | S1_32 | 0.918718797 |
| S1 | 32 | 4 | 340.3917 | 牛 | RFp | RF | S1_32 | 1.211836065 |
| S1 | 32 | 5 | 331.2249 | 牛 | RFp | RF | S1_32 | 1.010216850 |
| S1 | 32 | 6 | 311.1429 | 牛 | RFp | RF | S1_32 | 0.548290514 |
| S1 | 32 | 7 | 300.1738 | 牛 | RFp | RF | S1_32 | 0.283221394 |
| S1 | 32 | 8 | 302.1749 | 牛 | RFp | RF | S1_32 | 0.332294025 |
| S1 | 32 | 9 | 307.2229 | 牛 | RFp | RF | S1_32 | 0.454652178 |
| S1 | 32 | 10 | 296.0051 | 牛 | RFp | RF | S1_32 | 0.179936334 |
| S1 | 2 | 1 | 237.6748 | 链 | RFq | RF | S1_2 | -1.440974895 |
| S1 | 2 | 2 | 257.8014 | 链 | RFq | RF | S1_2 | -0.840639329 |
| S1 | 2 | 3 | 297.9747 | 链 | RFq | RF | S1_2 | 0.228916202 |
| S1 | 2 | 4 | 320.3587 | 链 | RFq | RF | S1_2 | 0.763865604 |
| S1 | 2 | 5 | 324.5692 | 链 | RFq | RF | S1_2 | 0.860302332 |
| S1 | 2 | 6 | 320.7375 | 链 | RFq | RF | S1_2 | 0.772593346 |
| S1 | 2 | 7 | 313.0966 | 链 | RFq | RF | S1_2 | 0.594520629 |
| S1 | 2 | 8 | 304.5275 | 链 | RFq | RF | S1_2 | 0.389570360 |
| S1 | 2 | 9 | 298.9819 | 链 | RFq | RF | S1_2 | 0.253839374 |
| S1 | 2 | 10 | 298.8253 | 链 | RFq | RF | S1_2 | 0.249968640 |
A function to plot f0 contours
p_cluster <- function(df_cluster, x, y = NULL, avg_line_width = 2.5){
p_cluster <- df_cluster %>%
ggplot(aes(x = time, y = norm_f0, group = ind_no, color = {{x}},
text = paste('speaker: ', speaker,
'\ntoken_no: ', citation_no,
'\ntoken: ', token,
'\ntime: ', time,
'\nnorm_f0: ', norm_f0))) +
geom_line(alpha = 0.2) +
scale_color_ptol() +
stat_summary(fun = mean, geom = "line", lwd = avg_line_width, aes(group = {{x}}), lty = 1) +
xlab("Normalised time") +
ylab("z-scores of log-f0") +
labs(color = "tone") +
scale_color_manual(values = c("#4477AA", "#CC6677", "#DDCC77", "#117733"))+
theme_minimal() +
theme(legend.position = "top",
text = element_text(family = 'Times New Roman', size = 20),
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 20)))
if (!is.null(y)) {
p_cluster <- p_cluster + facet_wrap(as.formula(paste("~", y)), ncol = 4, labeller = label_both)
}
return(p_cluster)
}
The plot below shows the f0 contours of the 4 non-checked tones (HH, HL, LH, RF) across all the 8 speakers. The solid lines are average contours, and the faint lines are individual contours for each token.
p_cluster(f0_mono_pre, citation_tone_sync,avg_line_width = 4)
The plot below shows the numbers of tokens collected for each tone.
f0_mono_count_all <- f0_mono_pre %>%
group_by(citation_tone_sync) %>%
count() %>%
mutate(n = n/10)
f0_mono_count_all
## # A tibble: 4 × 2
## # Groups: citation_tone_sync [4]
## citation_tone_sync n
## <chr> <dbl>
## 1 HH 182
## 2 HL 58
## 3 LH 39
## 4 RF 153
f0_mono_pre %>%
group_by(citation_tone_sync, speaker) %>%
count() %>%
mutate(n = n/10) %>%
ggplot(aes(x = citation_tone_sync, y = n, fill = speaker))+
geom_bar(stat="identity", position=position_dodge())+
geom_text(aes(label=n), vjust=1.6, color="black",
position = position_dodge(0.9), size=3.5)+
scale_fill_brewer(palette="Paired")
The plot below shows the f0 contours of the tones for each speaker. This plot is interactive, so you can:
There are some observations:
ggplotly(p_cluster(f0_mono_pre, citation_tone_sync, 'speaker', avg_line_width = 1.5),
tooltip = c('text', 'x'))